The conversation about AI in insurance customer service is moving beyond cost efficiency. As AI becomes mainstream, insurers are exploring how it can also improve the customer experience.

Agentic AI takes this potential a step further. Rather than simply generating an answer, a well-designed AI agent can understand a customer’s objective, coordinate actions across systems and people, and work toward the desired outcome, while escalating to a human when judgment is required.

That capability brings greater autonomy and a critical question: How can insurers give AI agents the authority to act while maintaining the human judgment customers need and trust?

When AI orchestrates the insurance customer journey

Agentic AI can shift insurance customer service from managing interactions to orchestrating outcomes. This will increasingly blur the boundaries between core and supporting functions, requiring insurers to rethink processes, data and technology together.

Consider a policyholder whose home has been damaged during a major storm. A conversational AI system may explain what the policyholder should do next. An agentic AI system could authenticate the customer, understand their coverage, open the claim and coordinate the journey. It could collect information, arrange services, initiate permitted payments and provide proactive updates while involving a human claim professional when judgment or additional support is required.

As routine work becomes increasingly automated, insurance professionals can focus their time on complex exceptions, vulnerable customers, disputes, judgment and oversight of AI-enabled journeys.

Beyond individual cases, agentic AI could also help insurers move from reactive to proactive service by identifying coverage gaps, preventing policy lapses, anticipating risks and addressing issues before they impact the customer.

But are insurers ready to make the shift? CGI’s 2026 Voice of Our Clients research shows that AI-enabled customer experience is a top priority, but delivering on that ambition depends on core modernization, automation and strong data foundations. Front-end innovation relies on back-end modernization. While 71% of insurance executives say digitalization is affecting their operating model, only 19% believe their operating model is sufficiently agile to support digital transformation.

With AI now widely accessible, the challenge for insurers is turning its potential into measurable, repeatable and controlled business outcomes.

Trust must be engineered, not asserted

Delegated authority has long been fundamental to insurance. Underwriters have limits, claims professionals have settlement authorities, and payments above defined thresholds require additional approval. The same principle should apply to agentic AI.

Each AI agent should operate within clearly defined boundaries: what it can access, recommend, change, approve or initiate, and when it must stop and involve a human.

Trust and governance therefore need to be designed from the start. Regulatory expectations are moving in the same direction. In Europe, key EU AI Act requirements, including transparency obligations, became applicable in August 2026. In the U.S., a growing number of states have adopted the NAIC Model Bulletin on AI use by insurers, while Canada's OSFI is strengthening expectations around AI and model risk.

The frameworks differ, but the direction is consistent: greater autonomy requires greater accountability, transparency, human oversight and operational resilience.

Why technology ecosystem choice matters for insurers

No single technology provider will supply every capability an insurer needs for an agentic operating model. The architecture may combine cloud infrastructure, foundation models, customer service platforms, core insurance systems, identity services, data platforms, cybersecurity controls and specialized industry solutions.

The same principle applies to conversational and agentic AI in customer service. CGI has delivered client initiatives with platforms such as NiCE Cognigy, but the starting point is not the technology itself. Technology choices need to reflect the customer experience an organization wants to create, its target operating model and the business outcomes it aims to achieve.

The governing principle is straightforward: technology selection should follow the target operating model and the desired business outcome, not the other way around.

A disciplined path from experimentation to scale

Insurers should not begin with the most complex claims or the most autonomous agents. A more measured approach starts with simple, bounded use cases that establish reusable foundations for trusted delegation before expanding autonomy.

Agentic AI will not eliminate the need for human insurance professionals. It will change where their time and judgment create the most value. It will also change what customers expect an insurer to know, explain and accomplish during a single interaction.

By combining agentic AI with modern customer platforms and trusted customer data, insurers can move beyond simply improving service productivity. They can begin to orchestrate customer journeys proactively, anticipate needs and coordinate actions across systems and teams, with the goal of improving customer satisfaction, loyalty and retention.

As insurers explore where agentic AI can create value, the conversation should start with the right balance of autonomy, human judgment and trust. Connect with me to discuss what that balance could look like for your organization.